Artificial intelligence-enabled screening for diabetic retinopathy: a real-world, multicenter and prospective study.

ABSTRACT:

Introduction

Early screening for diabetic retinopathy (DR) with an efficient and scalable method is highly needed to reduce blindness, due to the growing epidemic of diabetes. The aim of the study was to validate an artificial intelligence-enabled DR screening and to investigate the prevalence of DR in adult patients with diabetes in China.

Research design and methods

The study was prospectively conducted at 155 diabetes centers in China. A non-mydriatic, macula-centered fundus photograph per eye was collected and graded through a deep learning (DL)-based, five-stage DR classification. Images from a randomly selected one-third of participants were used for the DL algorithm validation.

Results

In total, 47 269 patients (mean (SD) age, 54.29 (11.60) years) were enrolled

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC7580048 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature